Director, AI-Driven Applications

Role Overview

• Define the enterprise AI application strategy, roadmap, and governance frameworks aligned with business objectives
• Lead the design and delivery of production AI applications using LLMs, multi-agent systems, retrieval-augmented generation (RAG), and fine-tuning pipelines
• Architect end-to-end agentic AI workflows: autonomous planning, tool use, memory management, and multi-agent orchestration
• Evaluate and select AI frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, custom) appropriate to enterprise scale and security requirements
• Champion responsible AI principles
• explainability, bias mitigation, auditability, and data privacy
• Design and govern enterprise data models supporting AI feature engineering, vector embedding stores, knowledge graphs, and real-time inference pipelines
• Define ontologies, taxonomies, and semantic layers that enable AI systems to reason over structured and unstructured enterprise data
• Oversee the architecture of data platforms including data lakes, lakehouses, streaming pipelines, and feature stores
• Establish data quality, lineage, and observability standards to ensure model reliability in production
• Own and evolve the enterprise architecture for AI integration across cloud, hybrid, and on-premise environments
• Drive architecture decisions across the full AI stack: model serving, API gateways, orchestration layers, observability, and security
• Align AI architecture with enterprise platforms and integration patterns (event-driven, microservices, API-first)
• Establish architecture review boards, design patterns, and reusable accelerators to scale AI delivery across business units
• Build, mentor, and lead a high-performing team of AI and Software engineers, data architects, and solution architects
• Partner with C-suite, business unit heads, and product leaders to identify and prioritize AI opportunities
• Represent the AI architecture function to executive stakeholders, board-level audiences, and external partners
• Drive a culture of continuous learning, experimentation, and engineering excellence.

Requirements

• 12+ years of progressive experience in software/data/AI architecture with 5+ years in a leadership role
• Proven delivery of enterprise-scale AI or ML applications in production environments
• Deep expertise in at least two major cloud platforms (AWS, Azure, GCP) and associated AI/ML services
• Strong background in data modelling and data platform design (relational, NoSQL, graph, vector)
• Demonstrated experience architecting agentic AI solutions using LLMs and orchestration frameworks
• Excellence in stakeholder communication, able to translate technical concepts for executive audiences.
• Experience in regulated industries (financial services, healthcare, government) with AI governance requirements
• Published research, patents, or open-source contributions in AI/ML
• Certifications: AWS Solutions Architect Professional, Google Cloud Professional Data Engineer, or equivalent
• Experience with TOGAF, Zachman, or other enterprise architecture frameworks.

Tech Stack

• AWS
• Azure
• Cloud
• Google Cloud Platform
• Microservices
• NoSQL

Benefits

• Health & Wellness: Health care coverage designed for the mind and body.
• Flexible Downtime: Generous time off helps keep you energized for your time on.
• Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
• Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
• Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
• Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.